Course Overview
- ›Installing Python (Windows/Mac)
- ›Installing VS Code
- ›Installing Python Extension
- ›Setting up Virtual Environment (venv)
- ›Installing NumPy, Pandas, Matplotlib
- ›Understanding Integrated Terminal
- ›Running Python Scripts
- ›Project Folder Structure
- ›What is Data Analytics?
- ›Types of Analytics
- ›Data Types and Formats
- ›Data Cleaning Concepts
- ›Analytics vs Data Science vs AI
- ›Industry Use Cases
- ›Variables and Data Types
- ›String Operations
- ›Conditional Statements
- ›Loops
- ›Type Casting
- ›Basic Debugging
- ›Lists and Operations
- ›Tuples
- ›Dictionaries
- ›Sets
- ›Comprehensions
- ›Nested Data Structures
- ›User-defined Functions
- ›Arguments and Return Values
- ›Lambda Functions
- ›Classes and Objects
- ›Inheritance
- ›Encapsulation
- ›File Handling
- ›CSV & JSON Handling
- ›Exception Handling
- ›Recursion
- ›Time Complexity Basics
- ›Google Colab Basics
- ›Creating and Managing Notebooks
- ›Markdown & Code Cells
- ›Anaconda Setup
- ›Conda Environments
- ›Jupyter Notebook
- ›Mean, Median, Mode
- ›Variance & Standard Deviation
- ›Probability Basics
- ›Normal Distribution
- ›Correlation Basics
- ›Bias-Variance Concept
- ›Database Basics
- ›DDL, DML Commands
- ›Primary & Foreign Keys
- ›CRUD Operations
- ›Subqueries
- ›Views
- ›Joins (Inner, Left, Right)
- ›Aggregate Functions
- ›Window Functions
- ›CTEs
- ›Stored Procedures
- ›Indexing
- ›Top 50 SQL Interview Questions
- ›Excel Interface
- ›Cell Referencing
- ›Sorting & Filtering
- ›Basic Formulas
- ›Logical Functions
- ›Lookup Functions
What we'll cover in this course:
- Setting up Coding Environment
- Introduction to Data Analytics
- Python Basics
- Python Data Structures
- Functions & OOP
- Advanced Python
- Google Colab & Anaconda
- Statistics for Data Analytics
- SQL Essentials
- SQL Advanced & Interview Prep
- Excel Foundations
- Excel Advanced Formulas
- Excel Dashboards
- NumPy for Data Analysis
- Pandas for Data Preprocessing
- Data Visualization with Matplotlib
- Advanced Visualization (Seaborn & Plotly)
- Power BI for Data Analysis
- Exploratory Data Analysis (EDA)
- Introduction to AI & ML Concepts
- Scikit-Learn & ML Setup
- Regression Algorithms
- Classification Algorithms
- Unsupervised Learning
- Model Optimization & Tuning
- Feature Engineering
- Time Series Analysis
- ML Deployment with Streamlit
- Prompt Engineering for Analysts
- AI Tools for Data Analysts
- Neural Network Fundamentals
- TensorFlow & Keras
- Convolutional Neural Networks
- RNN, LSTM & Sequence Models
- Computer Vision with OpenCV
- NLP Fundamentals
- Transformers & Hugging Face
- Generative AI Fundamentals
- Advanced Prompt Engineering
- LLM Integration & LangChain
- Building AI Applications
- Co-Pilot for Excel
- Power Query (Data Cleaning & Preprocessing)
- Power BI for Business Intelligence
- ChatGPT for Data Analysis
- Gemini for Data Visualization
- Gamma for Business Presentations
- Claude for Interactive Dashboards
- Business Strategy & Frameworks
- Excel Dashboard Building
- Database Design & Data Modeling
- Tableau for Business Intelligence
- Business Forecasting
- Financial Analytics
- A/B Testing & Experimentation
- Product & Marketing Analytics
- AI Case Study – Amazon
- AI Case Study – Netflix
- AI Case Study – Uber & Airbnb
- Business Documentation & BRD
- Agile & Scrum for Analysts
- Pitch Deck Creation using AI Tools
- Financial Modeling for Startups
- Capstone Project — Data Analytics
- Capstone Project — Machine Learning
- Capstone Project — Deep Learning / NLP
- GitHub & Kaggle Portfolio Building
- Resume & Interview Preparation
- High-Income Freelancing Skills
- Freelancing Platforms & Client Acquisition
- Business Analytics & Soft Skills
- Final Mastery & Career Launch
Technologies & Tools
